EO·AI LABS
Open Positions · 02 Roles · IIT Kanpur

Help build the planetary-intelligence stack.

EO·AI Labs turns Earth Observation into now-cast intelligence, scenario foresight, and real-time decision support. We're hiring two people to build the data and model infrastructure — and to carry the science to the partners who need it.

View the roles How to apply
About the Lab

EO·AI Labs is the applied research and commercialisation arm of the Space Technology Accelerator (STAr) at IIT Kanpur. We operate as three interlocking units — and these two roles sit across them. Both are based at IIT Kanpur and report to the Head of Lab, Dr. Abhay Gupta.

UNIT 01

Research Engine

Frontier methods and IP — foundation models, fusion, assimilation, agentic reasoning.

UNIT 02

Product Studio

Research translated into deployable APIs and data products.

UNIT 03

Market Access

Science connected to government, industry, and global research networks.

Two ways to join
ROLE 01

Data & Model Infrastructure Engineer (EO-AI)

Research Engine / Product Studio

You'll build the data and model infrastructure that everything else depends on — turning public Earth Observation archives, alternative data signals, and real-world models into a clean, queryable, production-grade foundation for now-casting and decision support. A hands-on building role for someone who codes fast, thinks in data, and uses modern AI coding assistants as a force multiplier.

What you'll do
  • Build and operate ingestion pipelines for public EO data (Sentinel-1/2, Landsat, MODIS, ISRO ResourceSat/Cartosat, Bhuvan) and alternative data signals (weather, IoT, market, mobility, and other non-traditional sources), harmonised to analysis-ready data.
  • Implement and extend the canonical data schema stack — STAC 1.1 catalogues, a GeoParquet + pgvector feature store, and validated inference records.
  • Develop, adapt, and fine-tune real-world models — from foundation-model embeddings and multi-sensor fusion to now-casting components — wired into reliable, testable pipelines.
  • Stand up the supporting infrastructure: data lakes, compute/MLOps workflows, evaluation harnesses, and monitoring.
  • Use AI coding assistants (e.g. Claude Code, Copilot, Cursor) fluently to prototype, refactor, and ship — and help set good practices for AI-assisted development.
What we're looking for
  • Master's or PhD student in Computer Science, or a recent graduate of an engineering discipline, with a strong coding and data-modeling background.
  • Strong programming (Python essential; SQL a plus) and sound software-engineering fundamentals — version control, testing, clean pipelines.
  • Demonstrated fluency with AI coding assistants and a track record of building real things quickly.
  • Comfort with data modeling and ML workflows: structuring messy data, fine-tuning models, reasoning about evaluation and uncertainty.
Nice to have
  • Geospatial / remote-sensing data, cloud platforms, vector databases, or MLOps (Kafka/Flink, containers, orchestration).
  • Familiarity with foundation models, data assimilation, or time-series / now-casting methods.
  • A portfolio, GitHub, or shipped projects we can look at.

Who thrives here: builders who want ownership of real infrastructure, energised by going from raw satellite bytes to a working signal — work that feeds decisions, not slide decks.

Apply for Role 01
ROLE 02

Research Partnerships & Commercialisation Developer (EO-AI)

Market Access / Research Engine

You'll connect the Lab's science to the people and institutions who can use it — developing research partnerships and commercialisation use-cases, and driving the academic and technical outreach that builds the Lab's reputation and pipeline. For someone with genuine applied-research aptitude who can move between a technical idea and the publication, proposal, or partner conversation that carries it forward.

What you'll do
  • Develop commercialisation use-cases — translating EO-AI research into concrete applications, proof-of-concept proposals, and value propositions for government, industry, finance, and research partners.
  • Build and steward research partnerships — joint supervision, collaborative grants (e.g. DST-SERB, ISRO RESPOND, ESA BIC), and co-development agreements.
  • Lead academic and technical outreach: co-author and coordinate publications, research agendas, white papers, briefs, and thought-leadership content; support conference and seminar engagement.
  • Help shape the narrative around the Lab's work — clear, credible positioning for technical and non-technical audiences alike.
  • Track opportunities (grants, calls, partner programmes) and help convert them into signed collaborations.
What we're looking for
  • Master's or PhD student, or a recent graduate, with demonstrated applied-research aptitude or experience.
  • Excellent written and verbal communication — able to explain technical work precisely and produce publication- and proposal-quality writing.
  • Initiative and relationship-building instinct: comfortable reaching out, following up, and building trust with partners.
  • Enough technical literacy to engage credibly with EO-AI research.
Nice to have
  • Background or interest in Earth Observation, AI/ML, environmental science, economics, or public policy.
  • Grant writing, technical writing, peer-reviewed publication, or research commercialisation / tech transfer.
  • A network in research, government, or industry relevant to EO-AI applications.

Who thrives here: people who want to build deep collaborations, not just citations — the bridge between brilliant science and the partners who need it.

Apply for Role 02
How to apply

Tell us why, and show us something.

Email us for either role. We respond to all substantive enquiries within 3 working days.

abhaygupta@iitk.ac.in Open email
Subject: “EO-AI Labs — [Role 01 / Role 02] Application”
Include
  • A short note on why this role and what you'd bring.
  • Your CV.
  • For Role 01, links to code/projects (GitHub or similar); for Role 02, a writing sample (publication, proposal, brief, or article).

Appointment type, duration, stipend/salary, start date, and on-site vs. hybrid will be confirmed during the process.